جستجوی مقالات مرتبط با کلیدواژه "p" در نشریات گروه "فنی و مهندسی"

The aerospace and automotive industries widely use composite materials due to their weight-to-strength ratios. One of the most significant problems with composites is repair and maintenance. This study attempts to repair glass epoxy composites. The repair process involves two stages: 1)optimization of the position of the hole and 2) repair work. To optimize the repair techniques, two distinct holes were performed: 1) at the center of the specimen and 2) at the edges of the specimen. As a result, the hole drilled at the center gives higher strength than the hole drilled at the edges. After the optimization, samples were repaired with a single hole in the center and peak loads of 60% and 90%. The cracked and delaminated areas were repaired with epoxy/hardener. The repaired samples were subjected to a three-point bending test, and the results were compared with the Neat GFRP samples. The results show that the curves of the repaired samples aligned with both the post and the residual flexural strength. The residual flexural strength of the 60% and 90% peak-loaded repaired samples retains about 47% and 76%, respectively.

In biomedical applications, particularly for tumor detection, the need for high-resolution imaging systems is critical. This paper presents the “S” parameter analysis of a three-layer stacked microstrip antenna with Defected Ground Structure (DGS) having a “+” shaped slot. The dimension of the antenna provides an enhanced performance ranging from 4.5-12 GHz. An aperture-coupled mechanism where a direct connection between feed and the FR-4 (Flame Retardant 4) substrate employing the need for three substrates having a dielectric constant (εr = 4.4) and having a thickness of 1.57mm each is utilized in this design. The composite material known as FR4 is structured with its fundamental layer consisting of fiberglass, woven into a thin, fabric-like sheet, providing essential structural support. This innermost layer of fiberglass imparts the necessary stability to FR4. It is then encased and secured by a flame-resistant epoxy resin. The antenna structure incorporates a parasitic patch as the topmost layer and an active patch that is placed below the substrate layer both of which incorporate slots for enhanced performance. The ground layer is sandwiched between the active layer and feedline which ensures separation between the two. Such a structure can help in optimizing both the radiating patch and the feedline independently. The performance of the designed antenna is studied for various slot configurations where the S- S-parameter analysis shows that the antenna provides wideband behavior which makes it suitable for biomedical applications like breast cancer detection. The S parameter analysis done in HFSS software shows a maximum return loss of -40dB which is performed for various slot configurations. The increasing demand for UWB communication systems underscores the critical importance of advanced antenna design to meet expanding data transmission requirements. The design of UWB antennas plays a crucial role in biomedical applications like breast cancer detection, where precise signal accuracy and penetration depth are essential for enhancing diagnostic efficacy and treatment monitoring.

Machine Learning has become prevalent nowadays for predicting data on the mechanical properties of various materials and is widely used in various polymeric applications. In the present study, Artificial Neural Network (ANN), a computational tool is used to predict the elastic modulus of a composite of longitudinally placed fiber-reinforced polymeric composite. The novelty in carried work is that the property prediction is carried out considering interphase and its properties. For this, tensile properties data of Longitudinally Placed Bamboo Fiber Reinforced Polyester Composite (LUDBPC), Longitudinally Placed Flax Fiber Reinforced Polyester Composite (LUDFPC) and Longitudinally Placed Jute Fiber Reinforced Polyester Composite (LUDJPC) has been procured to generate ANN models. The Levenberg-Marquardt training algorithm is used to generate the ANN models as it gives more accurate results compared to other ANN algorithms based on interphase properties data. The validation of ANN models was also carried out based on fresh experimental results of BPC/FPC by doing the fabrication with hand layup technique and testing of composites with a Universal Testing Machine (UTM). The present work signifies that the developed ANN models give accurate results with experimental results for the prediction of elastic modulus of composite (Ecl) and it can be used for the prediction of longitudinally placed fiber-reinforced composite and Ecl of BPC at volume fraction of fiber (vf):22% is 2248.75 MPa and Ecl of FPC at vf:10% is 3210.50 MPa.

In this manuscript, replacing traditional antennas with biodegradable PLA substrates aims to reduce e-waste in today's technologically advanced age. This work achieves its objectives by designing the miniaturized (56 x 56 x 1.6) mm3 hexagonal patch antenna with partial ground (18.2 x 52) mm2 and incorporating complementary split ring resonators (CSRRs) in the HFSS (High-Frequency Structure Simulator). This innovative approach combines unconventional antenna design with metamaterial technology to enhance antenna performance, making it flexible, lightweight, and suitable for multi-band applications. An evaluation of PLA compared to other substrates revealed that PLA is more suitable for its eco-friendliness, and the simulation result is also satisfactory for bandwidth, return loss, VSWR, directivity, efficiency, and other parameters. Additionally, the integration of taffeta fabric as a conductive patch material provided elasticity and enhanced wearability. Using this unique method, the proposed antenna resonates at multiband frequencies of 2.6 GHz, 8.6 GHz, 10.5 GHz, 12.4 GHz, and 15.3 GHz, which gives return losses of -26.84 dB, -22.16 dB, -29.87 dB, -39.43 dB, and -26.35 dB, respectively. In addition to its biocompatibility and achievement of the SAR threshold, the antenna serves as a long-term solution for multi-band wireless applications. This further advances the realm of environmentally friendly wearable technology.

Composites are widely used for different applications in engineering mainly due to their tailored benefits, durability, reduced maintenance, and enhanced performance. GFRP is a synthetic material that has revolutionized the aerospace industry, offering a high strength-to-weight ratio, fuel efficiency, and enhanced performance for advanced applications. In structures like aircraft components, holes or notches are often present due to design requirements or secondary joining processes through rivets or bolted connections, which leads to wear and tear. Further, how these materials behave under tensile loads near these openings is critical for ensuring the safety and reliability of such structures. In the present study, GFRP/Epoxy composite laminates are subjected to open hole tensile test under ON and OFF axis orientations. The effect of loading under different sequences was studied. The nature of failure near the hole region was reviewed and presented. It is noted that the dominant failure was LGM type under the ON-axis and different under the OFF-axis which is not limited to shear failure, interlaminar delamination, and mixed mode failures. These trends are noted for different hole dia, namely 6,9,12 and 18mm. The study also presents the nature of the stress-strain curve for both configurations. The OFF-axis specimens displayed a non-linear behavior to failure as compared to the On-axis type. While, the on-axis specimens showed a marked reduction in peak load and tensile strength as hole dia increased with reductions up to 65.23% and 63.57%, respectively relative to hole-less specimens. The inclined failure in off-axis specimens varied between 500 - 550. Further, the damage tolerance in OFF-axis samples was higher as compared to ON-axis specimens.

This paper presents a multi-scale strategy for the thermal simulation of frictional systems, such as brakes, considering the microscale properties of the polymer composites. A finite element model is supposed to model the system components at the macro scale. At the microscale, the thermal properties are evaluated to identify the effective thermal properties of the polymer composites. As regards wear, Archard's law is used with a wear rate coefficient depending on temperature. The micro-scale properties of the polymer composites are integrated into the macro-scale model using the COMSOL computational package. In the conducted study, it is determined that the contact temperature for organic disk brake pad material reaches the highest value at 727 K, followed by ceramic material pad at 691 K, and semi-metallic material at 689 K. Focusing on epoxy and epoxy-fiber composites, it is observed that the Kevlar-epoxy composite exhibits temperature performance characteristics comparable to those of the semi-metallic and ceramic materials, registering a contact temperature of 693 K. In contrast, both epoxy and epoxy-carbon fiber composites display significantly higher temperatures, with values of 1254 K and 944 K, respectively. Consequently, these findings suggest that Kevlar epoxy shows promise in serving as a future brake pad material for the automotive industry. The multi-scale study on different materials focusing on the use of computational results for replacing the traditional brake pad material with advanced composites is the novelty of the study.

Fossil fuels, a non-renewable source, supply more than 81% of the world’s primary energy and contribute heavily to global climate change. This paper represents a strategy to address the administration of forest bio residue in the northern Himalayan district of India. Uttarakhand state, the north part of India, is rich in bio residues such as Pine needles of Chir Pine (Pinus roxburghii). Every year during the summer, there is a forest fire breakout, mainly caused by these dry pine needles, which cover a forest floor and are highly flammable. This forest bio residue is renewable and is a potential energy source for rural livelihoods, which would also generate social business enterprises among the locals. This is an effort to develop a practical manual-operated briquetting machine (BM) capable of fabricating briquettes from forest waste. The primary materials utilized to make briquettes are pine needles and forest waste. The proposed method inculcates principles of compression molding along with necessary optimizations. Briquetting is one of the cheapest ways to harvest the destructive energy of pine needles in a clean and economically viable way. Briquetting machines reduce forest fires by reducing dependency on wood from forests for fuel while simultaneously lowering carbon emissions by using biomass or agricultural waste as alternative fuel sources. This dual benefit protects forests and helps battle climate change and local air pollution, making it a long-term option for environmental protection. The developed BM is one solution that can solve the dual purpose of climate change mitigation and employment. The designed and developed machine fabricates thirty-three briquettes per hour and is currently installed in the Uttarkashi district of Uttarakhand, India.

A propeller guard is an instrument that helps to avoid Unmanned Aerial Vehicles (UAVs) or drone damage. Commercially, they are made from an engineering plastic such as Acrylonitrile Butadiene Styrene (ABS). This work aims to introduce the hemp fiber-reinforced polypropylene composites as a new competitive material for propeller guards. In this study, polypropylene was thermally mixed with different ratios of hemp fibers by internal mixing at 190°C. Tensile and impact testing were carried out according to ASTM D638 and ASTM D256, respectively. The results showed that the high contents of hemp fibers can enhance the modulus of their composites. Polypropylene composite with 45 wt.% of hemp fibers obtained the highest modulus at 1169.4 MPa. Also, the impact resistances of these composites were higher while the fiber contents were increased. Furthermore, application in drone propeller guard was executed by SIMCENTER 3D software for proving their propeller protection performance of as-prepared composites. The results indicated that polypropylene and its hemp fibers-reinforced composites could be the materials for this drone propeller guard.

Wood/PLA biocomposite filament is a 3D printing material that blends Polylactic Acid (PLA), a biopolymer, with wood powder acting as reinforcement. This combination results in a sustainable 3D printing filament that has grown in popularity in recent years due to its eco-friendliness and the natural appearance of 3D-printed parts. To assess the suitability of wood/PLA biocomposite for various additive manufacturing applications, it is essential to determine its mechanical properties. This study employs fused deposition modeling (FDM) as the additive manufacturing process and focuses on assessing the mechanical properties (tensile, flexural, and impact) of 3D-printed biocomposite. The Taguchi L27 design of the experiments is utilized, and the key process parameters under consideration are infill pattern, layer thickness, raster angle, nozzle temperature, and infill density. A layer thickness of 0.3 mm and an infill density of 100% yielded the highest tensile strength of 42.46 MPa, flexural strength of 83.43 MPa, and impact strength of 44.76 J/m. The dataset has been carefully prepared to facilitate machine learning for both training and testing, and it contains the experimental results and associated process parameters. Four distinct machine learning algorithms have been selected for predictive modeling: Linear Regression, Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Adaptive Boosting (AdaBoost). Given the intricate nature of the dataset and the presence of nonlinear relationships between parameters, XGBoost and AdaBoost exhibited exceptional performance. Notably, the XGBoost model delivered the most accurate predictions. The results were assessed using the coefficient of determination (R2), and the achieved values for all observed mechanical properties were found to be greater than 0.99. The results signify the remarkable predictive capabilities of the machine learning model. This study provides valuable insights into using machine learning to predict the mechanical properties of 3D-printed wood/PLA composites, supporting progress in sustainable materials engineering and additive manufacturing.

The main aim of this research is to optimize the injection molding process parameters in order to mitigate the shrinkage of polypropylene (PP) spur gears. The methodology used integrated experimental approaches with artificial neural networks (ANN), and Taguchi methods to determine the optimal combination of injection molding parameters. The experimental data was used to create an ANN model using Matlab software that accurately predicts unseen data with a variation of less than 5%. The trained ANN model was further used to predict gear shrinkage in the context of Taguchi-based design of experiments. The investigation involved the use of Taguchi and analysis of variance techniques, determining that cooling time is the most important and relevant parameter. This is followed by packing time and melt temperature. The analysis revealed that the gears saw the least amount of shrinkage when the molding was carried out using the optimal combination of injection molding parameters.

Changes in the electric supply can significantly affect electronic devices since they are very sensitive. Due to a nonlinear system with multiple interconnected and unpredictable demands in the smart grid, the electricity system is facing several issues, including power quality, reactive power management, and voltage drop. To address these problems, a static synchronous compensator (STATCOM) is frequently used to compensate and correct the voltage level at the power bus voltage. In this study, an Artificial Neural Network (ANN) and GWO based controlled STATCOM has been developed to replace the traditional PI based controller and enhance the overall STATCOM performance. The ANN controller is preferred due to its simplicity, adaptability, resilience, and ability to consider the non-linearities of the power grid. To train the classifier offline, data from the PI controller was utilized. The MATLAB/Simulink software was employed to assess the effectiveness of STATCOM on a 25 Km transmission line during increased load and three faults. The combined results of the PI and ANN controllers indicate that the ANN controller significantly improves STATCOM efficiency under different operating conditions. Moreover, the ANN controller outperforms the traditional PI controller in terms of results.

Nowadays, with the detrimental impacts of air pollution on human health and its significant societal expenses, it has been imperative to utilize renewable energy sources (RESs) and energy storage systems (ESSs). This study introduces a new objective function aimed at achieving a long-term optimal plan where it contrasts the outcomes of meeting network load demand with and without the integration of renewable/non-renewable distributed energy resources (DERs). The analysis considers installation and operational costs, addressing uncertainties through Monte-Carlo and scenario-based methodologies. The proposed problem is structured as a convex optimization model. Simulations are conducted on the IEEE 33-bus system, showcasing the model’s efficacy through cost efficiency and reduced emission expenses. The study confirms that the investment in renewable energy resources and ESS units can be recouped in less than five years. It was observed that in the long-term, there is a cost reduction of 29.4\% when DER units are incorporated. Also, the emission cost for the horizon year is diminished by 43.2\% compared to the case where the DERs are absent.

The study of the geology of Russia’s Far East and Sakhalin projects has gained particular relevance for the Russian Federation due to their resource potential and proximity to export markets. The interaction between tectonic and sedimentary processes is especially visible on the Okhotsk Sea offshore. This study aims to clarify the geological conditions for the formation of reservoirs in the Daginskaya formation, which formed under the influence of the extensive paleo-delta system of the Amur River, based on a comprehensive analysis and processing of geological and seismic data. The main focus of the study is on the application of modern paleotectonic modeling technologies. Using Geoplat Pro-S and Petrel software, this research qualitatively examines the specific influence of structural-tectonic factors from the uplifts in the Kirinsky licensed area on reservoir distribution, employing stochastic inversion algorithms and paleotectonic analysis of paleo-history and paleotectonic cubes. The results confirm that the vaults of the uplifts acted as tectono-sedimentation barriers, restricting the advance of the Amur paleo-delta and the accumulation of high-capacity terrigenous reservoirs in the Daginskaya formation. Based on the findings, structural-tectonic zoning of the area was conducted, identifying blocks with distinct tectonic evolution. The results reaffirm the interdependence of tectonic and accumulation processes, the importance of comprehensive research, and provide critical insights into the geological mechanisms that led to the forming of productive formations on the Sakhalin offshore.

In conditions of gas pipelines operation, significant longitudinal deformations may occur at the sections adjacent to the receiving/ launching chambers of pig and diagnostic equipment. These deformations, caused by stress and temperature fluctuations, lead to undesirable deformations and damage of piping elements. To reduce the magnitude of longitudinal deformations the device of expansion joints is proposed. Geometric parameters of the expansion joint are determined based on the results of strength and stability calculations of the gas pipelines. The use of the software package START allowed to simulate the behavior of the pipeline before and after installation of the expansion joint and to analyze changes in longitudinal deformations.  An important part of the work is the methodology of calculation justification of the necessity to install such units to reduce longitudinal deformations. Optimization of the expansion joint design and calculation of its parameters contributes to the reliability of gas pipeline systems.

This study aims to optimize the flight endurance of a 12-passenger turboprop air taxi using two metaheuristic optimization algorithms: Grey Wolf Optimization (GWO) and Ant Colony Optimization (ACO). Initially, the gradient descent method was employed to estimate the aircraft's maximum weight. Subsequently, the aircraft's performance characteristics were utilized as design variables and flight endurance was optimized under specific constraints without altering the physical structure of the aircraft. The optimization process was implemented, and the results were evaluated and compared in terms of performance and efficiency. This research demonstrated that the two mentioned algorithms, utilizing random and collective strategies, were able to enhance the aircraft's efficiency. Additionally, the optimization of flight endurance for three real aircraft—Piper, Beechcraft, and Bombardier—was examined compared to their original endurance. In this context, the Ant Colony Optimization algorithm exhibited better performance than the Grey Wolf Optimization algorithm, which could have a positive impact on flight operations without refueling or the process of finding alternative airports.

This article discusses in detail the issue of killing gas wells with abnormally low reservoir pressure. The reason of discrepancies between the calculated data of the killing process according to the IWCF standard and the actual ones has been identified. It describes the physical mechanism of rupture of the liquid flow during injection. A mathematical formula describing the rupture of the fluid flow in the pipes is derived and verified using production data. The average deviation is 4.49%, which is acceptable for the problem being addressed. The authors proposed a mathematical model describing the killing of a gas well with abnormally low reservoir pressure. The killing process is analyzed at each stage. Verification calculations and comparison of their results with field data are presented. The average deviation of the calculated values from the actual ones falls within an acceptable range, amounting to 8.84%. The model is recommended for use in calculating the killing of gas wells with abnormally low reservoir pressure.

Formation damage is typically regarded as a detrimental phenomenon that necessitates effective treatment to optimize production efficiency and extend wellbore lifetime. This study introduces new standards to guide laboratory-based investigations into the efficiency of chemical solvents for mitigating formation damage in sandstone reservoirs, emphasizing pore-scale property changes and permeability recovery. Three sandstone core samples from an anonymous reservoir, characterized by varying geological and petrophysical properties, were subjected to initial damage through the injection of oil-based drilling fluids. Each sample was subsequently treated with a distinct chemical solvent to evaluate their respective efficiencies in restoring porosity and permeability. Advanced tomographic imaging and pore-scale analyses were employed to quantify changes before and after treatment, focusing on representative elementary volumes (REVs) along the samples. The findings highlight the critical influence of initial sedimentary heterogeneities on solvent efficiency. Variations in CT number, porosity, permeability, and tortuosity demonstrated spatial heterogeneity in solvent effectiveness along the injection pathway. Notably, tortuosity decreased across most REVs, particularly near the outlet, post-treatment, indicating improved fluid flow pathways. However, uniform and consistent improvements in porosity, pore size distribution, and permeability were not observed, underscoring the role of intrinsic geological variability. This study concludes that solvent efficiency is strongly influenced by the severity of initial sedimentary heterogeneities induced by formation damage, rather than being solely dependent on solvent type. To achieve reliable comparisons, future solvent performance evaluations must account for comparable levels of geological heterogeneity pre- and post-treatment. These findings provide actionable insights for optimizing solvent selection and developing more effective strategies for reservoir stimulation and formation damage remediation.

In modern conditions of the rapidly developing market of the mineral and raw materials complex the question of increasing the profitability of the enterprise is acute. However, cost reduction should not affect the safety of production works. In the present study the authors analyzed the activity of underground complex of Kirovsky mine of APATIT JSC, Kirovsk, Murmansk region. They identified the possibility of cost reduction through modernization of the mine (reduction of downtime during ventilation). We built a conceptual and mathematical model of the mine. In the work development of dust concentration control system was made, which is expressed in reducing the ventilation time from 60 to 30 minutes and achieving a more favorable dust concentration of 5 mg/m3, within generally accepted dust concentration of 8 mg/m3. Developed P, PI, PID regulators for regulating the ventilation system, determined the optimal regulator. We have developed a technical solution (patent №2799233) and implemented it in production. The present work is a report study on the fulfillment of the work within the framework of the thesis for the degree of Candidate of Technical Sciences.

In today's competitive market, manufacturers and service providers are continuously seeking ways to reduce costs and save time to gain a competitive edge. One of the most significant challenges they face is the vehicle routing problem (VRP), which is crucial due to its direct impact on the delivery time of services or products. Efficient vehicle routing not only enhances delivery performance but also optimizes the overall network, resulting in reduced operational costs. This study focuses on evaluating the VRP specifically for trucks while incorporating sustainability indicators into the analysis. The key sustainability indicators considered include social, economic, and environmental aspects. By integrating these indicators, the study aims to address multiple objectives simultaneously: reducing delivery time, minimizing costs, and mitigating the environmental impact of vehicle operations.The primary objective of this research is to minimize overall costs, fuel consumption, and route complexity associated with truck deliveries. Given the growing concern over environmental issues, there is a strong emphasis on improving methods to reduce greenhouse gas (GHG) emissions and streamline logistics processes. The research addresses these concerns by proposing a model that not only aims to enhance operational efficiency but also contributes to environmental protection and social responsibility.To achieve these objectives, the study employs advanced optimization techniques, specifically the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO). These methods are utilized to solve the VRP while balancing the trade-offs between various objectives, such as cost reduction, fuel efficiency, and route optimization.The results of the study indicate that the proposed model successfully improves aspects of environmental protection and social responsibility while simultaneously addressing economic concerns. The integration of sustainability indicators into the vehicle routing problem provides a comprehensive approach to optimizing logistics operations, highlighting the importance of considering environmental and social factors alongside economic performance.Overall, this research contributes to the field by offering a refined model for tackling the VRP, with a focus on sustainability. The findings underscore the potential for optimization algorithms to drive improvements in both operational efficiency and environmental stewardship, ultimately supporting more sustainable and socially responsible practices in the transportation and logistics industry.

A new type of closed-type lightning protection multi-chamber arrester named impulse quenching line lightning protection device (LLPD) used for protection of overhead power lines is described. After the passing of lightning current, the multi-chamber system of the arrester prevents the occurrence of a network short-circuit current due to the total voltage drop across several thousand series-connected spark gaps that significantly exceeds the applied network voltage in magnitude. The total operating time of the LLPD is less than 1 ms which is not sensitive for microprocessor and relay protection of overhead lines. A computational estimation of the emergency outage rate of double-circuit overhead power lines without an overhead ground wire resulting from lightning overvoltage was carried out. Number of current impulses used when arresters are tested for quenching capacity as well as their parameters were determined by the mathematical modeling using the statistical Monte Carlo method. Results of calculation that make it possible to determine the efficiency of lightning protection of double-circuit overhead lines with various placement schemes of the line lightning protection device LLPD-110 of the company Streamer Electric AG are presented in the conclusion.